HOUSTON, April 13, 2023 (GLOBE NEWSWIRE) -- Data Bridge Market research has recently released expansive research titled "Data Science Platform Market" which guarantees you will remain better informed than your competition.
A high-ranking data science platform market research report is a high-quality report having in-depth market research studies. It presents a definite solution to obtain market insights with which businesses can think about market place clearly and thereby take important decisions for the growth of the business. All the data, facts, figures and information is backed up by well-renowned analysis tools which include SWOT analysis and Porter’s Five Forces analysis. A number of steps are used while preparing the world-class data science platform market document by taking the inputs from a dedicated team of researchers, analysts and forecasters.
The market research analysis has been drawn in the top-notch data science platform market report with consistent knowledge of what the market expects, what is already available, the competitive environment, and what can be done to outshine the competition. The report is a complete overview of the market, covering various aspects including product definition, market segmentation based on various parameters, and the prevailing vendor landscape. This business research report helps to stay up-to-date about the whole market and also gives holistic view of the market. The universal data science platform market survey report is a professional in-depth study on the current state for the market and data science platform industry.
Global data science platform market was valued at USD 95.30 billion in 2021 and is expected to reach USD 686.71 billion by 2029, registering a CAGR of 28.00% during the forecast period of 2022-2029. In addition to the market insights such as market value, growth rate, market segments, geographical coverage, market players, and market scenario, the market report curated by the Data Bridge Market Research team includes in-depth expert analysis, import/export analysis, pricing analysis, production consumption analysis, and pestle analysis.
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A data science platform is a pre-packaged software program that offers the capabilities necessary for a data science project's whole life cycle. Platforms for data science are essential tools for data scientists. It makes model creation, model distribution, and data exploration possible. It offers a large-scale computing infrastructure and makes data preparation and visualization easier. Data science platforms offer a centralized platform that encourages user collaboration. Data science platforms act as a one-stop shop for data modelling since they include the APIs necessary for model creation and testing with little help from outside engineers.
The use of data science platforms by medium-sized and small-sized businesses has grown significantly in recent years. Additionally, firms are increasingly inclined to use cutting-edge technologies, such as automation and digitalization, which create a tons of data as well as complicated business procedures. As a result, the need for data science platform solutions is increasing, opening up profitable opportunities for businesses in the market.
This Data Science Platform Market report provides details of new recent developments, trade regulations, import-export analysis, production analysis, value chain optimization, market share, impact of domestic and localized market players, analyses opportunities in terms of emerging revenue pockets, changes in market regulations, strategic market growth analysis, market size, category market growths, application niches and dominance, product approvals, product launches, geographic expansions, technological innovations in the market. To gain more info on the Data Science Platform contact Data Bridge Market Research for an Analyst Brief, our team will help you take an informed market decision to achieve market growth.
Some of the major players operating in the data science platform market are:
- IBM (U.S.)
- DataRobot Inc., (U.S.)
- apheris AI GmbH (Germany)
- The Digital Talent Ecosystem (U.S.)
- Databand (Israel)
- dotData (U.S.)
- Explorium Inc., (U.S.)
- Noogata (Israel)
- Tecton Inc., (U.S.)
- Spell Designs Pty Ltd (U.S.)
- Arrikto Inc., (U.S.)
- Iterative (U.S.)
- Google Inc (U.S.)
- Microsoft (U.S.)
- SAS Institute Inc., (U.S.)
- Amazon Web Services, Inc. (U.S.)
- The MathWorks, Inc. (U.S.)
- Cloudera Inc., (U.S.)
- Teradata (U.S.)
- TIBCO Software Inc. (U.S.)
- ALTERYX, INC. (U.S.)
- RapidMiner (U.S.), Databricks (U.S.)
- Snowflake Inc., (U.S.)
- H2O.ai (U.S.)
- Altair Inc., (U.S.)
- Anaconda Inc., (U.S.)
- SAP SE (U.S.)
- Domino Data Lab Inc., (U.S.)
- Dataiku (U.S.)
Recent Developments
- In May 2021, Google changes the goal of Google Vertex AI, a new managed ML platform from Google Cloud, is to simplify the deployment and maintenance of AI models for developers. The fact that Google chose today to introduce Vertex demonstrates how important the company believes this new service is for a variety of developers. It is an unusual announcement at Google I/O, which typically concentrates on mobile and web developers and does not typically include much Google Cloud news.
- In September 2021, Latest MathWorks news the MathWorks 2021b product family for MATLAB and Simulink. Release 2021b (R2021b) of MATLAB and Simulink includes hundreds of new and updated features and functions, significant improvements, Code rewriting and block editing, as well as the ability to run Python commands and scripts from MATLAB. Simulink updates now allow users to perform many simulations for various scenarios from the Simulink Editor and make custom tabs for the Simulink Toolstrip.
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The report includes six parts, dealing with:
- Basic information
- The Asia Data Science Platform Market
- The North American Data Science Platform Market
- The European Data Science Platform Market
- The MEA Data Science Platform Market
- Market entry and investment feasibility
- The report conclusion
All the research report is made by using two techniques that are Primary and secondary research. There are various dynamic features of the business, like client need and feedback from the customers. Before (company name) curate any report, it has studied in-depth from all dynamic aspects such as industrial structure, application, classification, and definition.
Opportunities
- Rising Investment And Advancements In Technologies
The rising investment in research and development is estimated to generate lucrative opportunities for the market, which will further expand the data science platform market's growth rate in the future. Moreover, the advancements in technologies such as artificial intelligence (AI), machine learning (ML), and internet of things (IoT) further offer numerous growth opportunities within the market.
Data science platform Market Drivers:
This section deals with understanding the market drivers, advantages, opportunities, restraints and challenges. All of this is discussed in detail as below:
- The burgeoning growth of Big Data
The amount of data that enterprises collect is constantly rising due to the growth of social media, IoT, and multimedia, which have generated an overwhelming flow of data in both structured and unstructured forms. For instance, just the past two years have seen the creation of about 90% of the world's data. The growth rate of machine-based and human-generated data is generally 10 times greater than that of traditional corporate data. The growth rate of machine data is exponential and 50 times quicker. The majority of data is consumer driven and oriented. Today's "always-on" consumers produce the majority of data produced worldwide. The enormous growth in data presents chances for businesses to learn new things, which has led to a rise in the demand for fresh approaches. This in turn significantly influences the market for data science platforms.
- Numerous Benefits Offered by Data Science Platform
Data science platforms are currently being used more and more due to the various benefits offered by these platforms. The software offers open source tools significant flexibility and scalability of computing resources. Additionally, it is simple to align with different data architectures. In addition, the platform supports version control, enabling the data science team to collaborate on projects without losing recently completed work. Consequently, such advantages significantly aid market expansion over the forecast period.
Furthermore, the factors such as surge in reliance on machine learning coupled with the surge in inclination of enterprises toward data-intensive business strategies will accelerate the overall market expansion during the forecast period. Additionally surge in adoption of cloud-based solutions and services is anticipated to drive the growth rate of the data science platform market. The increase in the demand for analytical tools will further positively impact the market's growth rate during the forecast period.
Restraints/Challenges
- Uncertainty over the Business Issues
Businesses should research the issues they intend to use the data science platform for. Prior to having a good understanding of the business problem to be solved, choosing the mechanical technique of finding datasets and executing data analysis turns out to be less productive. Businesses using the data science platform to make wise decisions is extremely unhelpful. Even with a defined aim in mind, efforts are ineffective if firms' expectations from the installation of the data science platform are not in line with the objectives. This factor is projected to create various growth hindrances over the forecast period.
- Lack of Technical Expertise
Nowadays, businesses use sophisticated analytics methods including streaming analytics, machine learning, and predictive analytics. These methods are difficult and call for in-depth analytical expertise. Technical expertise as well as analytical and critical thinking abilities are necessary to develop an ML model. Many end users lack the personnel with the necessary abilities and information. Most of an organization's effort is spent collecting and correcting data generated from numerous sources. Not every employee that handles data must be knowledgeable in data science. To create a culture of data-driven decision-making, business expertise and the accompanying training are also necessary. Therefore, the dearth of trained staff or technical expertise is therefore estimated to be significant challenge for the data science platform market over the forecast period.
This data science platform market report provides details of new recent developments, trade regulations, import-export analysis, production analysis, value chain optimization, market share, the impact of domestic and localized market players, analyses opportunities in terms of emerging revenue pockets, changes in market regulations, strategic market growth analysis, market size, category market growths, application niches and dominance, product approvals, product launches, geographic expansions, technological innovations in the market. To gain more info on the data science platform market contact Data Bridge Market Research for an Analyst Brief, our team will help you take an informed market decision to achieve market growth.
To Get A Better Grasp Of The Market Analysis, Visit https://www.databridgemarketresearch.com/reports/global-data-science-platform-market
Data Science Platform Segmentation:
Component Type
- Platform
- Services
Function Division
- Marketing
- Sales
- Logistics
- Finance and Accounting
- Customer Support
- Business Operations
- Others
Deployment Model
- On-Premises
- Cloud-based
Organization Size
- Small and Medium-sized Enterprises (SMEs)
- Large Enterprises
End User Application
- Banking, Financial Services, and Insurance (BFSI)
- Telecom and IT
- Retail and E-commerce
- Healthcare and Life sciences
- Manufacturing
- Energy and Utilities
- Media and Entertainment
- Transportation and Logistics
- Government
Data Science Platform Country Level Analysis
The countries covered in the Data Science Platform report are South Africa, Saudi Arabia, U.A.E., Egypt, Israel, the Rest of Middle East and Africa, U.S., Canada, Mexico, Germany, U.K., France, Italy, Spain, Russia, Netherlands, Belgium, Switzerland, Turkey, Rest of Europe, China, Japan, India, South Korea, Australia, Singapore, Thailand, Malaysia, Indonesia, Philippines, Rest of Asia-Pacific, Brazil, Argentina and Rest of South America. North America dominates globally due to rising demand for advanced technologies and software design and development.
The country section of the report also provides individual market-impacting factors and market regulation changes that impact the market's current and future trends. Data points like downstream and upstream value chain analysis, technical trends, porter's five forces analysis, and case studies are some of the pointers used to forecast the market scenario for individual countries. Also, the presence and availability of global brands and their challenges faced due to large or scarce competition from local and domestic brands, the impact of domestic tariffs, and trade routes are considered while providing forecast analysis of the country data.
Data Science Platform Report Answers the Following Questions:
- How much revenue will the Data Science Platform generate by the end of the forecast period?
- Which market segment is expected to have the maximum market share?
- What are the influencing factors and their impact on the Data Science Platform market?
- Which regions are currently contributing the maximum share of the overall data science platform market?
- What indicators are likely to stimulate the Data Science Platform market?
- What are the main strategies of the major players in the Data Science Platform to expand their geographic presence?
- What are the main advances in the Data Science Platform market?
- How do regulatory standards affect the Data Science Platform market?
Table of Contents:
- Introduction
- Market Segmentation
- Executive Summary
- Premium Insights
- Global Data Science Platform Market: Regulations
- Market Overview
- Global Data Science Platform Market, By Component Type
- Global Data Science Platform Market, By Function Division
- Global Data Science Platform Market, By Deployment Model
- Global Data Science Platform Market, By Organization Size
- Global Data Science Platform Market, By End User Application
- Global Data Science Platform Market, By Region
- Global Data Science Platform Market: Company Landscape
- SWOT Analyses
- Company Profile
- Questionnaires
- Related Reports
To See the Detailed Table of Contents, Click here @ https://www.databridgemarketresearch.com/toc/?dbmr=global-data-science-platform-market
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